 ;;
 ;; We've already looked at `cast-with` and `cast-all`, which can be useful as output as well as input
 ;; processing functions.
-;; One of the first things we'll need is a function that takes a sequence of maps and turns it into a sequence
+;; Another important function we'll need is one that takes a sequence of maps and turns it into a sequence
 ;; of vectors since this is what most of our csv writing/formatting libraries will want.
 
 


(defn slurp-csv
  "This convenience function let's you `parse-and-process` csv data given a csv filename. Note that it is _not_
  lazy, and must read in all data so the file handle cna be closed."
  [csv-filename & {:as opts}]
  (let [rest-options (dissoc opts :parser-opts)]
    (with-open [in-file (io/reader csv-filename)]

;; <br/>
;; # One last example showing everything together
;;
;; Let's see how Semantic CSV works in the context of a little data pipeline.
;; We're going to thread data in, tranform into maps, run some computations for each row and assoc in,
;; then write the modified data out to a file, all lazily.
;; First let's show this with `clojure/data.csv`, which I find a little easier to use for writing.
